Mesh-Based Environmental Monitoring System for Residential Spaces

Abstract This paper presents the design and implementation of a Wi-Fi mesh network system for distributed monitoring of environmental parameters (temperature, humidity, atmospheric pressure, and air quality/VOC) in a residential setting. The system comprises one ROOT node acting as gateway and web server, and three SLAVE nodes for data acquisition. Built on the ESP32 platform using the painlessMesh library, the system operates fully locally without Internet dependency. A web interface accessible via captive portal enables real-time visualization, configurable alert thresholds, topology mapping, and CSV data export. Hardware integration includes BME680 sensors, OLED displays, autonomous 18650 battery power, and 3D-printed enclosures. Test results confirm coherent multi-room data differentiation and stable mesh.

Authors

Institutions

Publication Details

Journal
˜The œScientific Bulletin of Electrical Engineering Faculty
Published
2025-12-01
DOI
https://doi.org/10.2478/sbeef-2025-0020
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mesh-Based Environmental Monitoring System for Residential Spaces

A.C. Gheorghe
˜The œScientific Bulletin of Electrical Engineering Faculty
Air Quality Monitoring and Forecasting
article

Mesh-Based Environmental Monitoring System for Residential Spaces

A.C. Gheorghe
article en

Abstract

Abstract This paper presents the design and implementation of a Wi-Fi mesh network system for distributed monitoring of environmental parameters (temperature, humidity, atmospheric pressure, and air quality/VOC) in a residential setting. The system comprises one ROOT node acting as gateway and web server, and three SLAVE nodes for data acquisition. Built on the ESP32 platform using the painlessMesh library, the system operates fully locally without Internet dependency. A web interface accessible via captive portal enables real-time visualization, configurable alert thresholds, topology mapping, and CSV data export. Hardware integration includes BME680 sensors, OLED displays, autonomous 18650 battery power, and 3D-printed enclosures. Test results confirm coherent multi-room data differentiation and stable mesh.

˜The œScientific Bulletin of Electrical Engineering FacultyVol. 25(2)
Valahia University of Targoviste (RO)
Openalex Percentile: Top 35%
Air Quality Monitoring and Forecasting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.